Prediction of Cab Prices depending upon the distance and other factors.

This repository contains the source code for the Cab Fare Prediction Web Application. The application utilizes machine learning algorithms to predict cab fares based on various factors such as pickup location, drop location, time, date, no. of passengers etc.

Our machine learning project focuses on building and evaluating predictive models for cab fare prediction. We perform extensive data processing, cleaning, and feature extraction to prepare the dataset for model training. This project aims to predict cab fares accurately based on various input parameters such as location, no. of passengers and time.

This is a prediction machine learning model. In this project, my objective was to predict the fare of a cab based on time and daytime variance. I applied data cleaning, calculating the distance between the source and the destination. I implemented some ML regression algorithms and tested the score of the model

Data Science project on Cab Fare Prediction, Machine learning algorithms are used to develop a regression model. Problem Statement : The project is about a cab company who has done its pilot project and now they are looking to predict the fare for their future transactional cases. As, nowadays there are number of cab companies like Uber, Ola, Me…

Requirement is to apply analytics for fare prediction using historical data from the pilot project

Cab Fare Prediction